Kermit: linkage map guided long read assembly
Abstract Background With long reads getting even longer and cheaper, large scale sequencing projects can be accomplished without short reads at an affordable cost. Due to the high error rates and less mature tools, de novo assembly of long reads is still challenging and often results in a large col...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2019-03-01
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| Series: | Algorithms for Molecular Biology |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13015-019-0143-x |
| _version_ | 1818845699840671744 |
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| author | Riku Walve Pasi Rastas Leena Salmela |
| author_facet | Riku Walve Pasi Rastas Leena Salmela |
| author_sort | Riku Walve |
| collection | DOAJ |
| description | Abstract Background With long reads getting even longer and cheaper, large scale sequencing projects can be accomplished without short reads at an affordable cost. Due to the high error rates and less mature tools, de novo assembly of long reads is still challenging and often results in a large collection of contigs. Dense linkage maps are collections of markers whose location on the genome is approximately known. Therefore they provide long range information that has the potential to greatly aid in de novo assembly. Previously linkage maps have been used to detect misassemblies and to manually order contigs. However, no fully automated tools exist to incorporate linkage maps in assembly but instead large amounts of manual labour is needed to order the contigs into chromosomes. Results We formulate the genome assembly problem in the presence of linkage maps and present the first method for guided genome assembly using linkage maps. Our method is based on an additional cleaning step added to the assembly. We show that it can simplify the underlying assembly graph, resulting in more contiguous assemblies and reducing the amount of misassemblies when compared to de novo assembly. Conclusions We present the first method to integrate linkage maps directly into genome assembly. With a modest increase in runtime, our method improves contiguity and correctness of genome assembly. |
| first_indexed | 2024-12-19T05:33:49Z |
| format | Article |
| id | doaj.art-2c59a6c371f1469498d217042c874b6f |
| institution | Directory Open Access Journal |
| issn | 1748-7188 |
| language | English |
| last_indexed | 2024-12-19T05:33:49Z |
| publishDate | 2019-03-01 |
| publisher | BMC |
| record_format | Article |
| series | Algorithms for Molecular Biology |
| spelling | doaj.art-2c59a6c371f1469498d217042c874b6f2022-12-21T20:34:10ZengBMCAlgorithms for Molecular Biology1748-71882019-03-0114111010.1186/s13015-019-0143-xKermit: linkage map guided long read assemblyRiku Walve0Pasi Rastas1Leena Salmela2Department of Computer Science, Helsinki Institute for Information Technology HIIT, University of HelsinkiInstitute of Biotechnology, University of HelsinkiDepartment of Computer Science, Helsinki Institute for Information Technology HIIT, University of HelsinkiAbstract Background With long reads getting even longer and cheaper, large scale sequencing projects can be accomplished without short reads at an affordable cost. Due to the high error rates and less mature tools, de novo assembly of long reads is still challenging and often results in a large collection of contigs. Dense linkage maps are collections of markers whose location on the genome is approximately known. Therefore they provide long range information that has the potential to greatly aid in de novo assembly. Previously linkage maps have been used to detect misassemblies and to manually order contigs. However, no fully automated tools exist to incorporate linkage maps in assembly but instead large amounts of manual labour is needed to order the contigs into chromosomes. Results We formulate the genome assembly problem in the presence of linkage maps and present the first method for guided genome assembly using linkage maps. Our method is based on an additional cleaning step added to the assembly. We show that it can simplify the underlying assembly graph, resulting in more contiguous assemblies and reducing the amount of misassemblies when compared to de novo assembly. Conclusions We present the first method to integrate linkage maps directly into genome assembly. With a modest increase in runtime, our method improves contiguity and correctness of genome assembly.http://link.springer.com/article/10.1186/s13015-019-0143-xGenome assemblyLinkage mapsColoured overlap graph |
| spellingShingle | Riku Walve Pasi Rastas Leena Salmela Kermit: linkage map guided long read assembly Algorithms for Molecular Biology Genome assembly Linkage maps Coloured overlap graph |
| title | Kermit: linkage map guided long read assembly |
| title_full | Kermit: linkage map guided long read assembly |
| title_fullStr | Kermit: linkage map guided long read assembly |
| title_full_unstemmed | Kermit: linkage map guided long read assembly |
| title_short | Kermit: linkage map guided long read assembly |
| title_sort | kermit linkage map guided long read assembly |
| topic | Genome assembly Linkage maps Coloured overlap graph |
| url | http://link.springer.com/article/10.1186/s13015-019-0143-x |
| work_keys_str_mv | AT rikuwalve kermitlinkagemapguidedlongreadassembly AT pasirastas kermitlinkagemapguidedlongreadassembly AT leenasalmela kermitlinkagemapguidedlongreadassembly |